For example, there is recently developed a continuous glucose monitoring system (also referred to as CGM system) for continuously or intermittently quantifying a concentration of glucose in blood as analyte with a sensor unit embedded in the body of a subject to be tested. When a measurement signal is acquired via the sensor unit, various noises including electric noises or light quantity noises are typically mixed into the measurement signal. Thus, there are proposed various filtering techniques for effectively removing noise components in order to enhance an accuracy of quantifying a concentration of glucose.
JP 2005-131370 A proposes therein a method for removing noise components by use of a filtering algorithm (particularly Kalman filter) in a time domain. More specifically, it describes therein that an error covariance matrix is defined by a function of signal difference parameter (such as standard deviation) so that a filter coefficient is dynamically optimized.